Summary
In this chapter, you learned the fundamental and important concepts of machine learning classification, including types of classification, classification performance evaluation, cross-validation, and model tuning. You also learned about the simple, yet powerful, classifier Naïve Bayes. We went in depth through the mechanics and implementations of Naïve Bayes with a couple of examples, the most important one being the movie recommendation project.
Binary classification was the main talking point of this chapter, and multiclass classification will be the subject of the next chapter. Specifically, we will talk about SVMs for image classification.
